STrack: A Tool to Simply Track Bacterial Cells in Microscopy Time-Lapse Images

Todorov, Helena; Trabajo, Tania Miguel; Meer, van der Peter

doi:10.1128/msphere.00658-22

mSphere

2023

DOI: 10.1128/msphere.00658-22

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STrack: A Tool to Simply Track Bacterial Cells in Microscopy Time-Lapse Images

Helena Todorov

Tania Miguel Trabajo

van der Peter Meer

Abstract: Automated image analysis of growing prokaryotic cell populations becomes indispensable with larger data sets, such as derived by time-lapse microscopy. The tracking of the same individual cells and their daughter lineages is cumbersome and prone to errors in image alignment or poor resolution.

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2024

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Cited by 1 publication

References 33 publications

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Dimalis: A complete standalone pipeline to analyse prokaryotic cell growth from time-lapse imaging

Todorov,

Bentvelsen,

Ugolini

et al. 2024

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Real-time imaging of bacterial cell division, population growth and behaviour is essential for our understanding of microbial-catalyzed processes at the microscale. However, despite the relative ease by which high resolution imaging data can be acquired, the extraction of relevant cell features from images remains cumbersome. Here we present a versatile pipeline for automated extraction of bacterial cell features from standalone or time-resolved image series, with standardized data output for easy downstream processing. The input consist of phase-contrast images with or without additional fluorescence details, which are denoised to account for potential out-of-focus regions, and segmented to outline the morphologies of individual cells. Cells are then tracked over subsequent time frame images to provide genealogy or microcolony spatial information. We test the pipeline with eight different bacterial strains, cultured in microfluidics systems with or without nutrient flow, or on agarose miniature surfaces to follow microcolony growth. Examples of downstream processing in form of extraction of growth kinetic parameters or bistable cell differentiation are provided. The pipeline is wrapped in a Docker to facilitate installation, consistent processing and avoiding constant software updates.

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Dimalis: A complete standalone pipeline to analyse prokaryotic cell growth from time-lapse imaging

Todorov,

Bentvelsen,

Ugolini

et al. 2024

Preprint

Self Cite

View full text Add to dashboard Cite

show abstract

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STrack: A Tool to Simply Track Bacterial Cells in Microscopy Time-Lapse Images

Cited by 1 publication

References 33 publications

Dimalis: A complete standalone pipeline to analyse prokaryotic cell growth from time-lapse imaging

Dimalis: A complete standalone pipeline to analyse prokaryotic cell growth from time-lapse imaging

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